1. Field of the Invention
The present invention relates generally to computer software. More particularly, the present invention relates to software for processing measurement data.
2. Description of the Relevant Art
Technical Data Management (TDM) may include a large collection of functionality and operations performed by different applications and services in handling, processing and managing technical data from measurements, from simulations, and from various other technical data processing activities. The applications and services involved in TDM are typically within the operations of an engineering or scientific enterprise, or other organizational entity. The operations may include a wide variety of workflow processes related to technical data, including:                storing and retrieving technical data        exploring, searching and filtering technical datasets        managing and maintaining technical data stores        transmitting technical data to remote users        importing and exporting technical data from foreign systems        supporting network operations for TDM.Thus, the operational requirements associated with Technical Data Management represent a very complex organizational problem, whose solution has involved the use of numerous components and technologies, and whose challenge has involved the integration of those components and technologies.        
The field of Technical Data Management (TDM) may specifically include computer-based tools for acquiring, storing, and retrieving measurement data. As used herein, measurement data may represent a type of technical data acquired by a test and measurement application, e.g., via test and measurement hardware, such as data acquisition (DAQ) hardware or other hardware. In TDM involving measurements, it may be useful to store descriptive meta-data, which is associated with a given set of measurement data. One previous method for managing the complexity of TDM measurements has bundled the meta-data and the measurement data to provide self-describing measurement data.
For example, the Open Data Services (ODS) standard of the Association for Standardization of Automation and Measuring Systems (ASAM) specifies details for representations of the measurement and description data used in the automotive industry. ASAM-ODS generally defines a data model architecture (a method to describe the organization of data in a data store) and general methods to access data stores. An ATF (ASAM Transport Format) file, which is an ASCII representation of the ASAM-ODS data and data model, facilitates the exchange of data between different ASAM-ODS storage systems or other external systems. Measurement data (bulk data) can also be stored in binary files and linked to the ATF file.
Although the example of ASAM-ODS shows that some degree of standardizing the storage of meta-data among various applications is possible in one industry, there is little historical precedent indicating that any single standard data format, even if it were a self-describing format, could ever be widely adopted. The sheer volume and diversity of existing applications that process measurement data would involve an astronomical task of migration to any one standard, assuming such a standard could ever be agreed upon. Many operators of application programs would experience no benefits from a potential migration, but would incur major costs and disruption of their routine operations. Thus, the present situation, wherein various data formats are used by many different applications, is expected to reflect the future development of TDM.
Even if a single self-describing data format was adopted, TDM solutions for storing self-describing measurement data may have several drawbacks. For example, in distributed computer systems having multiple networked computers, finding the location of the stored data may be troublesome. In addition, the data format(s) of the stored data may vary or may not adhere to a given standard or policy defined for the organization. Resolving such issues, if at all possible, may often require customized programming for each application accessing the stored data. As customized code becomes increasingly necessary for integrating various components, TDM solutions tend to become systems that are expensive and time consuming to develop, that are difficult to maintain and use, and that do not scale efficiently.
Various TDM applications (such as those available from National Instruments Corporation) may be used to acquire and store measurements, or retrieve measurements from a data store for analysis and visualization. As noted above, the way TDM is often performed, each application is independently responsible for storing and retrieving data, usually in a different data format. In this type of environment, enterprise applications may concurrently access data stores which contain the measurement data. For example, two applications may access a first data store concurrently, or two applications may each access a different respective data stores concurrently. The various TDM applications can read and write to similar storage mechanisms such as files or databases.
While it is possible to build TDM solutions with common data stores, current implementations burden the developer of the application (for acquiring, visualizing, and analyzing measurement data) with the responsibility of maintaining a consistent data representation. In these kinds of TDM solutions, the various enterprise applications accessing a given data store must share an understanding of how the measurement data is represented, in turn requiring additional coordination and management effort that must be distributed among a large number of individual applications. As a result, these TDM methods, which involve applications directly accessing measurement data stores, may be difficult to scale across enterprise systems, because the responsibility for coordination and maintenance cannot be centrally enforced in a reliable, cost-effective manner that satisfies all individual requirements.